African Americans (AAs) are disproportionately burdened by type 2 diabetes mellitus (T2DM), with 19% of AA adults in the US affected as compared to 10% of whites. Because T2DM can be prevented or delayed with lifestyle and pharmaceutical interventions, it is crucial that we develop methods to identify high-risk persons before they develop T2DM. Risk prediction models are an effective tool for early identification of individuals who are at increased risk of developing T2DM. Available T2DM risk stratification tools however, were not developed using the current diagnostic criteria for T2DM which includes hemoglobin A1C (A1C) in the diagnosis of T2DM and current models have not been updated to include A1C as a predictor of T2DM risk. Further, of the existing diabetes prediction models, none have been developed in a population of AAs despite the fact that one of the strongest predictors of T2DM and one of the methods of diagnosing T2DM, A1C, varies substantially in AAs as compared to whites. Specifically, a number of studies have found higher levels of hemoglobin A1C (A1C) among AAs than whites that are not explained by differences in fasting glucose levels and AAs experience diabetic complications at lower values of A1C than whites. Current diagnostic guidelines, however, do not take into account known racial differences in the A1c-glycemia relationship. A potential explanation for these racial differences is the increased prevalence of sickle cell trait (SCT) in AAs as compared to whites. Sickle cell trait, a heritable disorder of the red blood cells that is more prevalent in African Americans, is hypothesized to further modify the A1c-glycemia relationship. Given that SCT may help to explain the biological differences in the A1c-glycemia relationship in AAs as compared to whites, we propose to, first, investigate the A1c-glycemia relationship in AAs with and without SCT (Aim #1) and, then, to develop (Aim #2) and validate (Aim #3) a series of risk prediction models which incorporate racial differences in A1c and examine the utility of incorporating SCT as a predictor of T2DM in order to better identify AAs at increased risk for developing T2DM. The proposed research will be carried out using existing data collected on AAs from two large cohort studies, the Jackson Heart Study and the Coronary Artery Risk Development in Young Adults study. This project will contribute to our understanding of the racial differences in the A1c-glucose relationship and will result in a series of externally validated T2DM prediction models that are sensitive to the differential prediction of A1C in AAs and that examine the potential role of SCT in T2DM prediction in AAs.